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Segmentation refers to the process of extracting meaningful regions from images. Such regions typically correspond to objects of interest or to their parts. The segmentation of medical images of soft tissues into regions (corresponding to meaningful biological structures such as cells and organs) is a difficult problem because of the large variety of their characteristics. Numerous segmentation methods have been proposed; their choice depend on the type of images, and of a priori knowledge about the objects to be detected. We present a method of segmentation that is combination of two attractive tools for segmentation, morphological segmentation and active contours. We describe the principle of morphological segmentation and active contours segmentation. We also present a method integrating the two approaches. Finally, we present three examples of the use of this method: segmentation of isolated nuclei for DNA quantification; segmentation of tumoral lobules in histological sections and extraction of the cerebellum in MR image of a human brain.